Developing relevant decision-support tools for policymakers to support large-scale implementation of climate-smart agriculture in the Global South is challenging given the great diversity in biophysical, socio-technical, and organizational conditions. This article describes a pilot exercise inspired by the recommendation domain literature that aimed at mapping, beyond “classical” biophysical and socio-technical variables, the institutional variables (i.e., the existence of policy incentives in national policy documents) that could influence the large-scale implementation of climate-smart agricultural practices. Four practices were considered: cereal-legume intercropping, fodder legume cultivation, farmer managed natural regeneration (FMNR) of Parkia biglobosa, and crop residue mulching. The biophysical and socio-technical variables were classified based on thresholds identified in the literature and mapped with a geographic information system. The policy documents considered were investment plans, adaptation plans for climate change, nationally determined contributions, and Technology Needs Assessments project reports. Sixteen policy documents for four countries were thoroughly reviewed and classified as unfavorable, intermediate, and favorable for the four selected practices, based on a decision tree built for that purpose. Our analysis shows that areas where biophysical, socio-technical, and institutional variables are aligned for the four practices considered are small, particularly for fodder legume cultivation and crop residue mulching. For cereal-legume intercropping, incentives from national policies strongly differ from one country to another while for FMNR of Parkia biglobosa policies are more homogeneously conducive across countries. Nonetheless, it was possible to identify areas where biophysical, socio-technical, and institutional dimensions of the transition toward climate-smart agriculture (CSA) were aligned, for example, cereal-legume intercropping in southern Mali. The delineating of favorable and unfavorable areas allows specific recommendations to be made for policymakers as levers for action differ in favorable, intermediate, and unfavorable zones. Based on the exploration made for the four practices, this study highlights the need for further articulations from local to national scale to implement CSA.

鉴于生物物理，社会技术和组织条件的多样性，为决策者开发相关的决策支持工具以支持在全球南方大规模实施气候智能型农业具有挑战性。本文介绍了一项受推荐领域文献启发的试点工作，该研究旨在针对可能影响大样本国家/地区的机构变量（即国家政策文件中存在政策激励措施）提供“经典”生物物理和社会技术变量之外的信息。大规模实施气候智能型农业实践。考虑了四种作法：谷物-豆类间作，豆类饲料的种植，大叶Parkia的农民管理的自然更新（FMNR），并覆盖农作物残渣。根据文献中确定的阈值对生物物理和社会技术变量进行分类，并通过地理信息系统进行映射。审议的政策文件包括投资计划，气候变化适应计划，国家确定的捐款以及技术需求评估项目报告。根据为此目的建立的决策树，对四个国家的十六份政策文件进行了彻底审查，并将其分类为对四种选定的实践不利，中等和不利。我们的分析表明，在考虑的四种实践中，生物物理，社会技术和机构变量保持一致的区域很小，特别是在豆科植物饲料种植和农作物残茬覆盖方面。对于谷物-豆类间作，大面积Parkia的政策在各个国家/地区的均质性更高。尽管如此，仍然有可能确定向气候智能农业（CSA）过渡的生物物理，社会技术和机构层面是一致的领域，例如马里南部的谷物-豆类间作。划定有利和不利区域可让政策制定者提出具体建议，因为在有利，中间和不利区域采取行动的杠杆各不相同。在对这四种实践进行探索的基础上，本研究强调了从地方到国家范围进一步实施CSA的必要性。